Posts Tagged ‘ Bayesian Core ’

Core [still] minus one…

September 22, 2012
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Core [still] minus one…

Another full day spent working with Jean-Michel Marin on the new edition of Bayesian Core (soon to be Bayesian Essentials with R!) and the remaining hierarchical Bayes chapter… I have reread and completed the regression and GLM chapters, sent to very friendly colleagues for a last round of comments. Now, I am essentially idle, waiting

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Core minus one!

September 9, 2012
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Core minus one!

Jean-Michel Marin visited me in Paris last week and, besides taking part in Pierre’s PhD defence, we made enough progress to close two more chapters of the new edition of Bayesian Core (soon to be Bayesian Essentials with R!) This follows the good work session we had in Carnon where we also completed two chapters

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Carnon [and Core, end]

June 15, 2012
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Carnon [and Core, end]

Yet another full day working on Bayesian Core with Jean-Michel in Carnon… This morning, I ran along the canal for about an hour and at last saw some pink flamingos close enough to take pictures (if only to convince my daughter that there were flamingos in the area!). Then I worked full-time on the spatial

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non-stationary AR(10)

January 18, 2012
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non-stationary AR(10)

In the revision of Bayesian Core on which Jean-Michel Marin and I worked together most of last week, having missed our CIRM break last summer (!), we have now included an illustration of what happens to an AR(p) time series when the customary stationarity+causality condition on the roots of the associated polynomial is not satisfied. 

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quantum forest

December 1, 2011
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quantum forest

Thanks to a link on R-bloggers, I was introduced to Luis Apiolaza’s blog, Quantum Forest, which covers data analyses and R comments he encounters in his research as a quantitative forester/geneticist. And he works at the University of Canterbury, Christchurch, where I first taught from Bayesian Core in 2006. Which may be why he chose

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understanding computational Bayesian statistics: a reply from Bill Bolstad

October 23, 2011
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understanding computational Bayesian statistics: a reply from Bill Bolstad

Bill Bolstad wrote a reply to my review of his book Understanding computational Bayesian statistics last week and here it is, unedited except for the first paragraph where he thanks me for the opportunity to respond, “so readers will see that the book has some good features beyond having a “nice cover”.” (!) I simply processed

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understanding computational Bayesian statistics

October 9, 2011
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understanding computational Bayesian statistics

I have just finished reading this book by Bill Bolstad (University of Waikato, New Zealand) which a previous ‘Og post pointed out when it appeared, shortly after our Introducing Monte Carlo Methods with R. My family commented that the cover was nicer than those of my own books, which is true. Before I launch into

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Number of components in a mixture

August 5, 2011
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Number of components in a mixture

I got a paper (unavailable online) to referee about testing for the order (i.e. the number of components) of a normal mixture. Although this is an easily spelled problem, namely estimate k in I came to the conclusion that it is a kind of ill-posed problem. Without a clear definition of what a component is,

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JSM 2011 [3]

August 2, 2011
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JSM 2011 [3]

Monday August 01 was the first full day of JSM 2011 and full is the appropriate word to describe the day! It started for me at 7am with a round table run by Marc Suchard on parallel computing (or at 3am if I am considering the time I woke up!). I was rather out of

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Core not in CiRM

July 27, 2011
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Core not in CiRM

Despite not enjoying this year the optimal environment of CiRM, we are still making good progress on the revision (or the R vision) of Bayesian Core. In the past two days, we went over Chapters 1 (Introduction), 2 (Normal Models), 5 (Capture-Recapture Experiments), and 6 (Mixture Models), with Chapters 3 (Regression), 4 (Generalised Linear Models)

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